An evolutionary advantage for extravagant honesty.

A game-theoretic model of handicap signalling over a pair of signalling channels is introduced in order to determine when one channel has an evolutionary advantage over the other. The stability conditions for honest handicap signalling are presented for a single channel and are shown to conform with the results of prior handicap signalling models. Evolutionary simulations are then used to show that, for a two-channel system in which honest signalling is possible on both channels, the channel featuring larger advertisements at equilibrium is favoured by evolution. This result helps to address a significant tension in the handicap principle literature. While the original theory was motivated by the prevalence of extravagant natural signalling, contemporary models have demonstrated that it is the cost associated with deception that stabilises honesty, and that the honest signals exhibited at equilibrium need not be extravagant at all. The current model suggests that while extravagant and wasteful signals are not required to ensure a signalling system's evolutionary stability, extravagant signalling systems may enjoy an advantage in terms of evolutionary attainability.

Navigating the perfect storm: research strategies for socialecological systems in a rapidly evolving world.

The 'Perfect Storm' metaphor describes a combination of events that causes a surprising or dramatic impact. It lends an evolutionary perspective to how social-ecological interactions change. Thus, we argue that an improved understanding of how social-ecological systems have evolved up to the present is necessary for the modelling, understanding and anticipation of current and future social-ecological systems. Here we consider the implications of an evolutionary perspective for designing research approaches. One desirable approach is the creation of multi-decadal records produced by integrating palaeoenvironmental, instrument and documentary sources at multiple spatial scales. We also consider the potential for improved analytical and modelling approaches by developing system dynamical, cellular and agent-based models, observing complex behaviour in social-ecological systems against which to test systems dynamical theory, and drawing better lessons from history. Alongside these is the need to find more appropriate ways to communicate complex systems, risk and uncertainty to the public and to policy-makers.

The robustness-fidelity trade-off in Grow When Required neural networks performing continuous novelty detection.

Novelty detection allows robots to recognise unexpected data in their sensory field and can thus be utilised in applications such as reconnaissance, surveillance, self-monitoring, etc. We assess the suitability of Grow When Required Neural Networks (GWRNNs) for detecting novel features in a robot's visual input in the context of randomised physics-based simulation environments. We compare, for the first time, several GWRNN architectures, including new Plastic architectures in which the number of activated input connections for individual neurons is adjusted dynamically as the robot senses a varying number of salient environmental features. The networks are studied in both one-shot and continuous novelty reporting tasks and we demonstrate that there is a trade-off, not unique to this type of novelty detector, between robustness and fidelity. Robustness is achieved through generalisation over the input space which minimises the impact of network parameters on performance, whereas high fidelity results from learning detailed models of the input space and is especially important when a robot encounters multiple novelties consecutively or must detect that previously encountered objects have disappeared from the environment. We propose a number of improvements that could mitigate the robustness-fidelity trade-off and demonstrate one of them, where localisation information is added to the input data stream being monitored.

Does attractiveness influence condom use intentions in women who have sex with men?

OBJECTIVES: Attractiveness judgements have been shown to affect interpersonal relationships. The present study explored the relationships between perceived attractiveness, perceived sexual health status, condom use intentions and condom use resistance in women. SETTING: The study data were collected using an online questionnaire. PARTICIPANTS: 480 English-speaking women who have sex with men, between 18-32 years old. OUTCOME MEASURES: Women were asked to rate the attractiveness of 20 men on the basis of facial photographs, to estimate the likelihood that each man had a sexually transmitted infection (STI), and to indicate their willingness to have sex with each man without a condom. Condom resistance tactics were also measured and their influence on condom use intentions was assessed. RESULTS: The more attractive a man was judged to be, the more likely it was that participants were willing to have sex with him (r (478) = 0.987, p < .001). Further, the more attractive a man was judged to be, the less likely women were to intend to use a condom during sex (r = -0.552, df = 478, p = .007). The average perceived STI likelihood for a man had no significant association with his average perceived attractiveness or with participants' average willingness to have sex with him. The more attractive a participant judged herself to be, the more she believed that, overall, men are likely to have a STI (r = 0.103, df = 478, p < .05). CONCLUSIONS: Women's perceptions of men's attractiveness influence their condom use intentions; such risk biases should be incorporated into sexual health education programmes and condom use interventions.

Information Exchange Design Patterns for Robot Swarm Foraging and Their Application in Robot Control Algorithms.

In swarm robotics, a design pattern provides high-level guidelines for the implementation of a particular robot behaviour and describes its impact on swarm performance. In this paper, we explore information exchange design patterns for robot swarm foraging. First, a method for the specification of design patterns for robot swarms is proposed that builds on previous work in this field and emphasises modular behaviour design, as well as information-centric micro-macro link analysis. Next, design pattern application rules that can facilitate the pattern usage in robot control algorithms are given. A catalogue of six design patterns is then presented. The patterns are derived from an extensive list of experiments reported in the swarm robotics literature, demonstrating the capability of the proposed method to identify distinguishing features of robot behaviour and their impact on swarm performance in a wide range of swarm implementations and experimental scenarios. Each pattern features a detailed description of robot behaviour and its associated parameters, facilitated by the usage of a multi-agent modeling language, BDRML, and an account of feedback loops and forces that affect the pattern's applicability. Scenarios in which the pattern has been used are described. The consequences of each design pattern on overall swarm performance are characterised within the Information-Cost-Reward framework, that makes it possible to formally relate the way in which robots acquire, share and utilise information. Finally, the patterns are validated by demonstrating how they improved the performance of foraging e-puck swarms and how they could guide algorithm design in other scenarios.

Minimally Sufficient Conditions for the Evolution of Social Learning and the Emergence of Non-Genetic Evolutionary Systems.

Social learning, defined as the imitation of behaviors performed by others, is recognized as a distinctive characteristic in humans and several other animal species. Previous work has claimed that the evolutionary fixation of social learning requires decision-making cognitive abilities that result in transmission bias (e.g., discriminatory imitation) and/or guided variation (e.g., adaptive modification of behaviors through individual learning). Here, we present and analyze a simple agent-based model that demonstrates that the transition from instinctive actuators (i.e., non-learning agents whose behavior is hardcoded in their genes) to social learners (i.e., agents that imitate behaviors) can occur without invoking such decision-making abilities. The model shows that the social learning of a trait may evolve and fix in a population if there are many possible behavioral variants of the trait, if it is subject to strong selection pressure for survival (as distinct from reproduction), and if imitation errors occur at a higher rate than genetic mutation. These results demonstrate that the (sometimes implicit) assumption in prior work that decision-making abilities are required is incorrect, thus allowing a more parsimonious explanation for the evolution of social learning that applies to a wider range of organisms. Furthermore, we identify genotype-phenotype disengagement as a signal for the imminent fixation of social learners, and explain the way in which this disengagement leads to the emergence of a basic form of cultural evolution (i.e., a non-genetic evolutionary system).

Using Computer Simulations for Investigating a Sex Education Intervention: An Exploratory Study.

BACKGROUND: Sexually transmitted infections (STIs) are ongoing concerns. The best method for preventing the transmission of these infections is the correct and consistent use of condoms. Few studies have explored the use of games in interventions for increasing condom use by challenging the false sense of security associated with judging the presence of an STI based on attractiveness. OBJECTIVES: The primary purpose of this study was to explore the potential use of computer simulation as a serious game for sex education. Specific aims were to (1) study the influence of a newly designed serious game on self-rated confidence for assessing STI risk and (2) examine whether this varied by gender, age, and scores on sexuality-related personality trait measures. METHODS: This paper undertook a Web-based questionnaire study employing between and within subject analyses. A Web-based platform hosted in the United Kingdom was used to deliver male and female stimuli (facial photographs) and collect data. A convenience sample group of 66 participants (64%, 42/66) male, mean age 22.5 years) completed the Term on the Tides, a computer simulation developed for this study. Participants also completed questionnaires on demographics, sexual preferences, sexual risk evaluations, the Sexual Sensation Seeking Scale (SSS), and the Sexual Inhibition Subscale 2 (SIS2) of the Sexual Inhibition/Sexual Excitation Scales-Short Form (SIS/SES - SF). RESULTS: The overall confidence of participants to evaluate sexual risks reduced after playing the game (P<.005). Age and personality trait measures did not predict the change in confidence of evaluating risk. Women demonstrated larger shifts in confidence than did men (P=.03). CONCLUSIONS: This study extends the literature by investigating the potential of computer simulations as a serious game for sex education. Engaging in the Term on the Tides game had an impact on participants' confidence in evaluating sexual risks.

Infection dynamics on spatial small-world network models.

The study of complex networks, and in particular of social networks, has mostly concentrated on relational networks, abstracting the distance between nodes. Spatial networks are, however, extremely relevant in our daily lives, and a large body of research exists to show that the distances between nodes greatly influence the cost and probability of establishing and maintaining a link. A random geometric graph (RGG) is the main type of synthetic network model used to mimic the statistical properties and behavior of many social networks. We propose a model, called REDS, that extends energy-constrained RGGs to account for the synergic effect of sharing the cost of a link with our neighbors, as is observed in real relational networks. We apply both the standard Watts-Strogatz rewiring procedure and another method that conserves the degree distribution of the network. The second technique was developed to eliminate unwanted forms of spatial correlation between the degree of nodes that are affected by rewiring, limiting the effect on other properties such as clustering and assortativity. We analyze both the statistical properties of these two network types and their epidemiological behavior when used as a substrate for a standard susceptible-infected-susceptible compartmental model. We consider and discuss the differences in properties and behavior between RGGs and REDS as rewiring increases and as infection parameters are changed. We report considerable differences both between the network types and, in the case of REDS, between the two rewiring schemes. We conclude that REDS represent, with the application of these rewiring mechanisms, extremely useful and interesting tools in the study of social and epidemiological phenomena in synthetic complex networks.

Does attractiveness influence condom use intentions in heterosexual men? An experimental study.

OBJECTIVES: Judgements of attractiveness have been shown to influence the character of social interactions. The present study sought to better understand the relationship between perceived attractiveness, perceived sexual health status and condom use intentions in a heterosexual male population. SETTING: The study employed an electronic questionnaire to collect all data, during face-to-face sessions. PARTICIPANTS: 51 heterosexual, English-speaking men aged between 18 and 69 years. OUTCOME MEASURES: Men were asked to rate the attractiveness of 20 women on the basis of facial photographs, to estimate the likelihood that each woman had a sexually transmitted infection (STI) and to indicate their willingness to have sex with or without a condom with each woman. RESULTS: The more attractive a woman was judged to be on average, the more likely participants would be willing to have sex with her (p<0.0001) and the less likely they were to intend to use a condom during sex (p<0.0001). Multivariate analysis revealed that higher condom use intentions towards a particular woman were associated with lower ratings of her attractiveness (p<0.0005), higher ratings of her STI likelihood (p<0.0001), the participant being in an exclusive relationship (p=0.002), having a less satisfactory sex life (p=0.015), lower age (p=0.001), higher number of sexual partners (p=0.001), higher age at first intercourse (p=0.002), higher rates of condomless sex in the last 12 months (p<0.043) and lower confidence in their ability to assess whether or not a woman had an STI (p=0.001). The more attractive a participant judged himself to be, the more he believed that other men like him would engage in condomless sex (p=0.001) and the less likely he was to intend to use a condom himself (p=0.02). CONCLUSIONS: Male perceptions of attractiveness influence their condom use intentions; such risk biases could profitably be discussed during sex education sessions and in condom use promotion interventions.

The implementation of electronic services: planned or organic growth?

The literature on innovation suggests that projects are successful when rigorous project management is mixed judiciously with 'organic' development. This paper argues that organic growth can play a substantial role in the implementation of electronic services in healthcare settings. Evidence for organic growth is presented, based on a study of email use. Methods are presented for investigating email use in health service settings in the National Health Service (NHS) in Bradford, England. Geographical information systems (GIS) outputs and social network analyses are presented. The results demonstrate a fivefold increase in the use of email over a 13-month period, which is shown to be largely independent of the growth in the number of organisations using the network. They also demonstrate a marked increase in the complexity of the patterns of email use over the period.

Natural convection of a two-dimensional Boussinesq fluid does not maximize entropy production.

Rayleigh-Bénard convection is a canonical example of spontaneous pattern formation in a nonequilibrium system. It has been the subject of considerable theoretical and experimental study, primarily for systems with constant (temperature or heat flux) boundary conditions. In this investigation, we have explored the behavior of a convecting fluid system with negative feedback boundary conditions. At the upper and lower system boundaries, the inward heat flux is defined such that it is a decreasing function of the boundary temperature. Thus the system's heat transport is not constrained in the same manner that it is in the constant temperature or constant flux cases. It has been suggested that the entropy production rate (which has a characteristic peak at intermediate heat flux values) might apply as a selection rule for such a system. In this work, we demonstrate with Lattice Boltzmann simulations that entropy production maximization does not dictate the steady state of this system, despite its success in other, somewhat similar scenarios. Instead, we will show that the same scaling law of dimensionless variables found for constant boundary conditions also applies to this system.

Wasps, termites, and waspmites: distinguishing competence from performance in collective construction.

We introduce a distinction between algorithm performance and algorithm competence and argue that bio-inspired computing should characterize the former rather than the latter. To exemplify this, we explore and extend a bio-inspired algorithm for collective construction influenced by paper wasp behavior. Despite its being provably general in its competence, we demonstrate limitations on the algorithm's performance. We explain these limitations, and extend the algorithm to include pheromone-mediated behavior typical of termites. The resulting hybrid waspmite algorithm shares the generality of the original wasp algorithm, but exhibits improved performance and scalability.

Stability in flux: community structure in dynamic networks.

The structure of many biological, social and technological systems can usefully be described in terms of complex networks. Although often portrayed as fixed in time, such networks are inherently dynamic, as the edges that join nodes are cut and rewired, and nodes themselves update their states. Understanding the structure of these networks requires us to understand the dynamic processes that create, maintain and modify them. Here, we build upon existing models of coevolving networks to characterize how dynamic behaviour at the level of individual nodes generates stable aggregate behaviours. We focus particularly on the dynamics of groups of nodes formed endogenously by nodes that share similar properties (represented as node state) and demonstrate that, under certain conditions, network modularity based on state compares well with network modularity based on topology. We show that if nodes rewire their edges based on fixed node states, the network modularity reaches a stable equilibrium which we quantify analytically. Furthermore, if node state is not fixed, but can be adopted from neighbouring nodes, the distribution of group sizes reaches a dynamic equilibrium, which remains stable even as the composition and identity of the groups change. These results show that dynamic networks can maintain the stable community structure that has been observed in many social and biological systems.

Sensitivity and stability: a signal propagation sweet spot in a sheet of recurrent centre crossing neurons.

In this paper we demonstrate that signal propagation across a laminar sheet of recurrent neurons is maximised when two conditions are met. First, neurons must be in the so-called centre crossing configuration. Second, the network's topology and weights must be such that the network comprises strongly coupled nodes, yet lies within the weakly coupled regime. We develop tools from linear stability analysis with which to describe this regime in terms of the connectivity and weight strengths of a network. We use these results to examine the apparent tension between the sensitivity and instability of centre crossing networks.

Shedding light on plant competition: modelling the influence of plant morphology on light capture (and vice versa).

A plant's morphology is both strongly influenced by local light availability and, simultaneously, strongly influences this local light availability. This reciprocal relationship is complex, but lies at the heart of understanding plant growth and competition. Here, we develop a sub-individual-based simulation model, cast at the level of interacting plant components. The model explicitly simulates growth, development and competition for light at the level of leaves, branches, etc., located in 3D space. In this way, we are able to explore the manner in which the low-level processes governing plant growth and development give rise to individual-, cohort-, and community-level phenomena. In particular, we show that individual-level trade-offs between growing up and growing out arise naturally in the model, and robustly give rise to cohort-level phenomena such as self-thinning, and community processes such as the effect of ecological disturbance on the maintenance of biodiversity. We conclude with a note on our methodology and how to interpret the results of simulation models such as this one.

Exploring the dynamics of adaptation with evolutionary activity plots.

Evolutionary activity statistics and their visualization are introduced, and their motivation is explained. Examples of their use are described, and their strengths and limitations are discussed. References to more extensive or general accounts of these techniques are provided.

Picture this: the state of the art in visualization for complex adaptive systems.

Visualization has an increasingly important role to play in scientific research. Moreover, visualization has a special role to play within artificial life as a result of the informal status of its key explananda: life and complexity. Both are poorly defined but apparently identifiable via raw inspection. Here we concentrate on how visualization techniques might allow us to move beyond this situation by facilitating increased understanding of the relationships between an ALife system's (low-level) composition and organization and its (high-level) behavior. We briefly review the use of visualization within artificial life, and point to some future developments represented by the articles collected within this special issue.

The role of logistic constraints in termite construction of chambers and tunnels.

In previous models of the building behaviour of termites, physical and logistic constraints that limit the movement of termites and pheromones have been neglected. Here, we present an individual-based model of termite construction that includes idealized constraints on the diffusion of pheromones, the movement of termites, and the integrity of the architecture that they construct. The model allows us to explore the extent to which the results of previous idealized models (typically realised in one or two dimensions via a set of coupled partial differential equations) generalize to a physical, 3-D environment. Moreover we are able to investigate new processes and architectures that rely upon these features. We explore the role of stigmergic recruitment in pillar formation, wall building, and the construction of royal chambers, tunnels and intersections. In addition, for the first time, we demonstrate the way in which the physicality of partially built structures can help termites to achieve efficient tunnel structures and to establish and maintain entrances in royal chambers. As such we show that, in at least some cases, logistic constraints can be important or even necessary in order for termites to achieve efficient, effective constructions.

Combating coevolutionary disengagement by reducing parasite virulence.

While standard evolutionary algorithms employ a static, absolute fitness metric, coevolutionary algorithms assess individuals by their performance relative to populations of opponents that are themselves evolving. Although this arrangement offers the possibility of avoiding long-standing difficulties such as premature convergence, it suffers from its own unique problems, cycling, over-focusing and disengagement. Here, we introduce a novel technique for dealing with the third and least explored of these problems. Inspired by studies of natural host-parasite systems, we show that disengagement can be avoided by selecting for individuals that exhibit reduced levels of "virulence", rather than maximum ability to defeat coevolutionary adversaries. Experiments in both simple and complex domains are used to explain how this counterintuitive approach may be used to improve the success of coevolutionary algorithms.

The view from elsewhere: perspectives on ALife modeling.

Many artificial life researchers stress the interdisciplinary character of the field. Against such a backdrop, this report reviews and discusses artificial life, as it is depicted in, and as it interfaces with, adjacent disciplines (in particular, philosophy, biology, and linguistics), and in the light of a specific historical example of interdisciplinary research (namely cybernetics) with which artificial life shares many features. This report grew out of a workshop held at the Sixth European Conference on Artificial Life in Prague and features individual contributions from the workshop's eight speakers, plus a section designed to reflect the debates that took place during the workshop's discussion sessions. The major theme that emerged during these sessions was the identity and status of artificial life as a scientific endeavor.